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Background The clinical utility of personal genomic information in identifying individuals at increased risks for dyslipidemia and cardiovascular diseases remains unclear. Methods We used data from Biobank Japan (n = 70,657–128,305) and developed novel East Asian-specific genome-wide polygenic risk scores (PRSs) for four lipid traits. We validated (n = 4271) and subsequently tested associations of these scores with 3-year lipid changes in adolescents (n = 620), carotid intima-media thickness (cIMT) in adult women (n = 781), dyslipidemia (n = 7723), and coronary heart disease (CHD) (n = 2374 cases and 6246 controls) in type 2 diabetes (T2D) patients. Results Our PRSs aggregating 84–549 genetic variants (0.251 r) r − 103 P − 75) and 3-year lipid changes (1.4 × 10− 6 P β ± SE = 0.052 ± 0.002), 11.7% in TG (β ± SE = 0.111 ± 0.006), 5.8% in HDL-C (β ± SE = 0.057 ± 0.003), and 8.4% in LDL-C (β ± SE = 0.081 ± 0.004) per one standard deviation increase in the corresponding PRS. However, their predictive power was attenuated in T2D patients (0.183 r − 3 P − 10 P β ± SE = 0.011 ± 0.005, Ptrend = 0.0182). Independent of conventional risk factors, the quintile of PRSs for TC [OR (95% CI) = 1.07 (1.03–1.11)], TG [OR (95% CI) = 1.05 (1.01–1.09)], and LDL-C [OR (95% CI) = 1.05 (1.01–1.09)] were significantly associated with increased risk of CHD in T2D patients (4.8 × 10− 4 P Conclusions The PRSs derived and validated here highlight the potential for early genomic screening and personalized risk assessment for cardiovascular disease.

Increasing childhood obesity and young-onset diabetes have made clinically distinguishing between type 1 diabetes (T1D) and type 2 diabetes (T2D) more difficult. A Genetic risk score (GRS) for T1D was developed in European populations, with good discrimination of diabetes type. Here, we aim to evaluate T1D-GRS in a Han-Chinese cohort. We utilized whole genome genotyping data for 533 nondiabetic controls, 182 patients with T1D, and 6,209 patients with T2D. We computed the T1D-GRS for each subject using 30 T1D associated SNPs. The mean ages of the controls, T1D, and T2D subjects were 47±11, 32±15, and 57±13 years, respectively. Violin plots of the GRS for the 3 groups are shown in the Figure, along with p-values. The mean GRS across the controls, T1D, and T2D were 0.242, 0.256, and 0.242, respectively. The area under the curve (AUC) for GRS in T1D vs. T2D was 0.677 (95% CI: 0.635-0.718), and 0.678 (95% CI: 0.631-0.725) for T1D patients vs. controls. We conclude that T1D-GRS detects significant differences in T1D genetic risk between T1D and non-T1D in a Han-Chinese population, with subjects with T1D having a higher score. Further refinement incorporating single nucleotide polymorphisms (SNPs) specific for a Han-Chinese population is currently underway, and is expected to further improve classification of T1D in Han-Chinese. Disclosure R. Wan: None. S.A. Sharp: None. C.H.T. Tam: None. M.N. Weedon: None. J.C. Chan: None. W. Hagopian: Consultant; Self; Novo Nordisk Inc. R.A. Oram: None. R.C. Ma: Advisory Panel; Self; AstraZeneca. Stock/Shareholder; Self; GemVCare. Other Relationship; Self; AstraZeneca, Bayer Healthcare Pharmaceuticals Inc., Merck & Co., Inc., Novo Nordisk A/S, Pfizer Inc., Sanofi-Aventis, Tricida Inc. Funding Research Grants Council (T12-402/13N); Research Impact Fund (CUR4012-18)

Summary Although skeletal muscle cells can be generated from human induced pluripotent stem cells (iPSCs), transgene-free protocols include only limited options for their purification and expansion. In this study, we found that fluorescence-activated cell sorting-purified myogenic progenitors generated from healthy controls and Pompe disease iPSCs can be robustly expanded as much as 5 × 1011-fold. At all steps during expansion, cells could be cryopreserved or differentiated into myotubes with a high fusion index. In vitro, cells were amenable to maturation into striated and contractile myofibers. Insertion of acid α-glucosidase cDNA into the AAVS1 locus in iPSCs using CRISPR/Cas9 prevented glycogen accumulation in myotubes generated from a patient with classic infantile Pompe disease. In vivo, the expression of human-specific nuclear and sarcolemmar antigens indicated that myogenic progenitors engraft into murine muscle to form human myofibers. This protocol is useful for modeling of skeletal muscle disorders and for using patient-derived, gene-corrected cells to develop cell-based strategies., Highlights • Transgene-free protocol for generation and expansion of myogenic progenitors • Differentiation into contractile skeletal muscle cells in vitro • Correction of glycogen accumulation in Pompe disease using CRISPR/cas9 • Contribution to muscle regeneration in vivo, Van der Wal et al. present a robust protocol for the transgene-free generation and purification of myogenic progenitors from human iPSCs and for their expansion up to 5 × 1011-fold. After gene editing in vitro, these myogenic progenitors matured into contractile skeletal muscle cells, reversing Pompe disease pathology. In vivo, myogenic progenitors contributed to muscle regeneration.

Motivation Optical mapping is a technique for capturing fluorescent signal patterns of long DNA molecules (in the range of 0.1–1 Mbp). Recently, it has been complementing the widely used short-read sequencing technology by assisting with scaffolding and detecting large and complex structural variations (SVs). Here, we introduce a fast, robust and accurate tool called OMBlast for aligning optical maps, the set of signal locations on the molecules generated from optical mapping. Our method is based on the seed-and-extend approach from sequence alignment, with modifications specific to optical mapping. Results Experiments with both synthetic and our real data demonstrate that OMBlast has higher accuracy and faster mapping speed than existing alignment methods. Our tool also shows significant improvement when aligning data with SVs. Availability and Implementation OMBlast is implemented for Java 1.7 and is released under a GPL license. OMBlast can be downloaded from https://github.com/aldenleung/OMBlast and run directly on machines equipped with a Java virtual machine. Supplementary information Supplementary data are available at Bioinformatics online

Summary Adult stem cells are essential for tissue regeneration. However, the mechanisms underlying the activation of quiescent adult stem cells remain elusive. Using skeletal muscle stem cells, also called satellite cells (SCs), we demonstrate prevalent intron retention (IR) in the transcriptome of quiescent SCs (QSCs). Intron-retained transcripts found in QSCs are essential for fundamental functions including RNA splicing, protein translation, cell-cycle entry, and lineage specification. Further analysis reveals that phosphorylated Dek protein modulates IR during SC quiescence exit. While Dek protein is absent in QSCs, Dek overexpression in vivo results in a global decrease of IR, quiescence dysregulation, premature differentiation of QSCs, and undermined muscle regeneration. Moreover, IR analysis on hundreds of public RNA-seq data show that IR is conserved among quiescent adult stem cells. Altogether, we illustrate IR as a conserved post-transcriptional regulation mechanism that plays an important role during stem cell quiescence exit.

International audience; Adult tissue repair and regeneration require stem-progenitor cells that can self-renew and generate differentiated progeny. Skeletal muscle regenerative capacity relies on muscle satellite cells (MuSCs) and their interplay with different cell types within the niche. However, our understanding of skeletal muscle tissue cellular composition is limited. Here, using a combined approach of single-cell RNA sequencing and mass cytometry, we precisely mapped 10 different mononuclear cell types in adult mouse muscle. We also characterized gene signatures and determined key discriminating markers of each cell type. We identified two previously understudied cell populations in the interstitial compartment. One expresses the transcription factor scleraxis and generated tenocytes in vitro. The second expresses markers of smooth muscle and mesenchymal cells (SMMCs) and, while distinct from MuSCs, exhibited myogenic potential and promoted MuSC engraftment following transplantation. The blueprint presented here yields crucial insights into muscle-resident cell-type identities and can be exploited to study muscle diseases.

Adult tissue repair and regeneration require the activation of resident stem/progenitor cells that can self-renew and generate differentiated progeny. The regenerative capacity of skeletal muscle relies on muscle satellite cells (MuSCs) and their interplay with different cell types within the niche. Yet, our understanding of the cells that compose the skeletal muscle tissue is limited and molecular definitions of the principal cell types are lacking. Using a combined approach of single-cell RNA-sequencing and mass cytometry, we precisely mapped the different cell types in adult skeletal muscle tissue and highlighted previously overlooked populations. We identified known functional populations, characterized their gene signatures, and determined key markers. Among the ten main cell populations present in skeletal muscle, we found an unexpected complexity in the interstitial compartment and identified two new cell populations. One express the transcription factor Scleraxis and generate tenocyte-like cells. The second express smooth muscle and mesenchymal cell markers (SMMCs). While distinct from MuSCs, SMMCs are endowed with myogenic potential and promote MuSC engraftment following transplantation. Our high-dimensional single-cell atlas uncovers principles of an adult tissue composition and can be exploited to reveal unknown cellular sub-fractions that contribute to tissue regeneration.

Adult tissue repair and regeneration require the activation of resident stem and progenitor cells that can self-renew and generate differentiated progeny. The regenerative capacity of skeletal muscle relies on muscle satellite cells (MuSCs) and their interplay with different cell types within the niche. However, our understanding of the cells that compose skeletal muscle tissue is limited and molecular definitions of the principal cell types are lacking. Here, using a novel combined approach of single-cell RNA-sequencing and mass cytometry, we precisely mapped 10 different cell types in adult mouse skeletal muscle, including two previously unidentified populations. We also characterized the gene signatures and determined the key discriminating markers of each cell type. We found an unexpected complexity in the interstitial compartment, wherein two new cell populations were identified. One population expressed the transcription factor Scleraxis and generated tenocytes in vitro. The second population expressed smooth muscle and mesenchymal cell (SMMC) markers and, while distinct from MuSCs, exhibited myogenic potential and promoted MuSC engraftment following transplantation. The blueprint presented here yields crucial insights into muscle-resident cell type identities and can be exploited to study muscle ageing and diseases.

Use of multilocus sequence typing may help identify new strains in at-risk populations., Chlamydia trachomatis causes a high number of sexually transmitted infections worldwide, but reproducible and precise strain typing to link partners is lacking. We evaluated multilocus sequence typing (MLST) for this purpose by detecting sequence types (STs) concordant for the ompA genotype, a single-locus typing standard. We tested samples collected during April 2000–October 2003 from members of established heterosexual partnerships (dyads) in the Indianapolis, Indiana, USA, area who self-reported being coital partners within the previous 30 days. C. trachomatis DNA from 28 dyads was tested by MLST; sequences were aligned and analyzed for ST and phylogenetic relationships. MLST detected 9 C. trachomatis STs, 4 unique to Indianapolis; STs were identical within each dyad. Thirteen unique strains were identified; 9 (32%) dyads harbored novel recombinant strains that phylogenetically clustered with strains comprising the recombinants. The high rate of novel C. trachomatis recombinants identified supports the use of MLST for transmission and strain diversity studies among at-risk populations.

Lateral gene transfer (LGT) is essential for generating between-strain genomic recombinants of Chlamydia trachomatis to facilitate the organism's evolution. Because there is no reliable laboratory-based gene transfer system for C. trachomatis , in vitro generation of recombinants from antibiotic-resistant strains is being used to study LGT. However, selection pressures imposed on in vitro recombinants likely affect statistical properties of recombination relative to naturally occurring clinical recombinants, including prevalence at particular loci. We examined multiple loci for 16 in vitro -derived recombinants of ofloxacin- and rifampin-resistant L 1 and D strains, respectively, grown with both antibiotics, and compared these with the same sequenced loci among 11 clinical recombinants. Breakpoints and recombination frequency were examined using phylogenetics, bioinformatics, and statistics. In vitro and clinical isolates clustered perfectly into two groups, without misclassification, using Ward's minimum variance based on breakpoint data. As expected, gyrA (confers ofloxacin resistance) and rpoB (confers rifampin resistance) had significantly more breakpoints among in vitro recombinants than among clinical recombinants ( P < 0.0001 and P = 0.02, respectively, using the Wilcoxon rank sum test). Unexpectedly, trpA also had significantly more breakpoints for in vitro recombinants ( P < 0.0001). There was also significant selection at other loci. The strongest bias was for ompA in strain D ( P = 3.3 × 10 −8 ). Our results indicate that the in vitro model differs statistically from natural recombination events. Additional genomic studies are needed to determine the factors responsible for the observed selection biases at unexpected loci and whether these are important for LGT to inform approaches for genetically manipulating C. trachomatis .

Motivation: The growth of next-generation sequencing means that more effective and efficient archiving methods are needed to store the generated data for public dissemination and in anticipation of more mature analytical methods later. This article examines methods for compressing the quality score component of the data to partly address this problem. Results: We compare several compression policies for quality scores, in terms of both compression effectiveness and overall efficiency. The policies employ lossy and lossless transformations with one of several coding schemes. Experiments show that both lossy and lossless transformations are useful, and that simple coding methods, which consume less computing resources, are highly competitive, especially when random access to reads is needed. Availability and implementation: Our C++ implementation, released under the Lesser General Public License, is available for download at http://www.cb.k.u-tokyo.ac.jp/asailab/members/rwan. Contact: rwan@cuhk.edu.hk Supplementary information: Supplementary data are available at Bioinformatics online.

Summary: Insertional mutagenesis from virus infection is an important pathogenic risk for the development of cancer. Despite the advent of high-throughput sequencing, discovery of viral integration sites and expressed viral fusion events are still limited. Here, we present ViralFusionSeq (VFS), which combines soft-clipping information, read-pair analysis and targeted de novo assembly to discover and annotate viral–human fusions. VFS was used in an RNA-Seq experiment, simulated DNA-Seq experiment and re-analysis of published DNA-Seq datasets. Our experiments demonstrated that VFS is both sensitive and highly accurate. Availability: VFS is distributed under GPL version 3 at http://hkbic.cuhk.edu.hk/software/viralfusionseq Contact: tf.chan@cuhk.edu.hk Supplementary information: Supplementary data are available at Bioinformatics Online

Chlamydia trachomatis is an obligate intracellular bacterium that causes a diversity of severe and debilitating diseases worldwide. Sporadic and ongoing outbreaks of lymphogranuloma venereum (LGV) strains among men who have sex with men (MSM) support the need for research on virulence factors associated with these organisms. Previous analyses have been limited to single genes or genomes of laboratory-adapted reference strain L2/434 and outbreak strain L2b/UCH-1/proctitis. We characterized an unusual LGV strain, termed L2c, isolated from an MSM with severe hemorrhagic proctitis. L2c developed nonfusing, grape-like inclusions and a cytotoxic phenotype in culture, unlike the LGV strains described to date. Deep genome sequencing revealed that L2c was a recombinant of L2 and D strains with conserved clustered regions of genetic exchange, including a 78-kb region and a partial, yet functional, toxin gene that was lost with prolonged culture. Indels (insertions/deletions) were discovered in an ftsK gene promoter and in the tarp and hctB genes, which encode key proteins involved in replication, inclusion formation, and histone H1-like protein activity, respectively. Analyses suggest that these indels affect gene and/or protein function, supporting the in vitro and disease phenotypes. While recombination has been known to occur for C. trachomatis based on gene sequence analyses, we provide the first whole-genome evidence for recombination between a virulent, invasive LGV strain and a noninvasive common urogenital strain. Given the lack of a genetic system for producing stable C. trachomatis mutants, identifying naturally occurring recombinants can clarify gene function and provide opportunities for discovering avenues for genomic manipulation., IMPORTANCE Lymphogranuloma venereum (LGV) is a prevalent and debilitating sexually transmitted disease in developing countries, although there are significant ongoing outbreaks in Australia, Europe, and the United States among men who have sex with men (MSM). Relatively little is known about LGV virulence factors, and only two LGV genomes have been sequenced to date. We isolated an LGV strain from an MSM with severe hemorrhagic proctitis that was morphologically unique in tissue culture compared with other LGV strains. Bioinformatic and statistical analyses identified the strain as a recombinant of L2 and D strains with highly conserved clustered regions of genetic exchange. The unique culture morphology and, more importantly, disease phenotype could be traced to the genes involved in recombination. The findings have implications for bacterial species evolution and, in the case of ongoing LGV outbreaks, suggest that recombination is a mechanism for strain emergence that results in significant disease pathology.

The main way of analyzing biological sequences is by comparing and aligning them to each other. It remains difficult, however, to compare modern multi-billionbase DNA data sets. The difficulty is caused by the nonuniform (oligo)nucleotide composition of these sequences, rather than their size per se. To solve this problem, we modified the standard seed-and-extend approach (e.g., BLAST) to use adaptive seeds. Adaptive seeds are matches that are chosen based on their rareness, instead of using fixed-length matches. This method guarantees that the number of matches, and thus the running time, increases linearly, instead of quadratically, with sequence length. LAST, our open source implementation of adaptive seeds, enables fast and sensitive comparison of large sequences with arbitrarily nonuniform composition.

Background Visualization tools allow researchers to obtain a global view of the interrelationships between the probes or experiments of a gene expression (e.g. microarray) data set. Some existing methods include hierarchical clustering and k-means. In recent years, others have proposed applying minimum spanning trees (MST) for microarray clustering. Although MST-based clustering is formally equivalent to the dendrograms produced by hierarchical clustering under certain conditions; visually they can be quite different. Methods HAMSTER (Helpful Abstraction using Minimum Spanning Trees for Expression Relations) is an open source system for generating a set of MSTs from the experiments of a microarray data set. While previous works have generated a single MST from a data set for data clustering, we recursively merge experiments and repeat this process to obtain a set of MSTs for data visualization. Depending on the parameters chosen, each tree is analogous to a snapshot of one step of the hierarchical clustering process. We scored and ranked these trees using one of three proposed schemes. HAMSTER is implemented in C++ and makes use of Graphviz for laying out each MST. Results We report on the running time of HAMSTER and demonstrate using data sets from the NCBI Gene Expression Omnibus (GEO) that the images created by HAMSTER offer insights that differ from the dendrograms of hierarchical clustering. In addition to the C++ program which is available as open source, we also provided a web-based version (HAMSTER+) which allows users to apply our system through a web browser without any computer programming knowledge. Conclusion Researchers may find it helpful to include HAMSTER in their microarray analysis workflow as it can offer insights that differ from hierarchical clustering. We believe that HAMSTER would be useful for certain types of gradient data sets (e.g time-series data) and data that indicate relationships between cells/tissues. Both the source and the web server variant of HAMSTER are available from http://hamster.cbrc.jp/.

New DNA sequencing technologies have achieved breakthroughs in throughput, at the expense of higher error rates. The primary way of interpreting biological sequences is via alignment, but standard alignment methods assume the sequences are accurate. Here, we describe how to incorporate the per-base error probabilities reported by sequencers into alignment. Unlike existing tools for DNA read mapping, our method models both sequencer errors and real sequence differences. This approach consistently improves mapping accuracy, even when the rate of real sequence difference is only 0.2%. Furthermore, when mapping Drosophila melanogaster reads to the Drosophila simulans genome, it increased the amount of correctly mapped reads from 49 to 66%. This approach enables more effective use of DNA reads from organisms that lack reference genomes, are extinct or are highly polymorphic.